You should be discussing this with your thesis advisor. If the area is not one that he or she is familiar with, you may have to find a co-advisor, or accept that you may not get as much help as you'd like. See multiple Q&A on this at Academia.SE.
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mkennedyDec 15 '14 at 17:29

Being able to take high order geometry with a lot of detail and simplifying it for a coarser detail map, without dropping important features, is darned difficult. For example a chain of small lakes visible at 1:50,000 should not be shown at all at 1:500,000, yet the watercourse that connects them should remain visible, and continuous.

wouldn't it be wonderful if the computer noticed that the geometries of layers X,Y & Z were very similar to each other, nearly always following the same trends, and offered to conflate/merge them, or keep the others in lockstep when one is changed?

@user19400: the contribution you made should be a comment to the answer rather than an inline edit. Use the [edit xx time ago] link to retrieve your text. While it does continue and support the theme, it is a new thought. It would also be good to point to the results of that research, or the names of the papers, if that is at all possible.
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matt wilkieJun 24 '13 at 16:56

So far as I know, MetaCarta is the only company talking about or providing a service which attempts to automatically georeference any document based on it's content. For example it knows Mark Twain's Tom Sawyer lives along the Mississippi River. This is a rich field and there is a lot of room for more players and implementations.

Human perception and cognition is limited and those limits are becoming increasingly problematic as the volume and variety of information continues to explode in amount and complexity. How can the tools of space and location and representation be leveraged to transform this cacophony of data into pieces understandable, and actionable, to the human mind?

Parallel GIS processing was hot 12 years ago, but seems to have slowly faded. (The link to the "GIS Parallel Architectures Lab" on this page is broken, I wonder if the lab still exists). With so much interest in multicore and cloud, it seems like there should be growing interest in parallel geoprocessing too.

A lot of people say the best way to go parallel is via Functional Programming. That might be a good area, but it seems to suffer the same academic stigma that Artificial Intelligence was never able to shed.

To what "academic" stigma are you referring? Since functional programming underlies many extremely popular and successful computing platforms in academia, including R (on the FOSS side) and Mathematica (commercial), any such stigma surely hasn't attached to the actual use of functional programming!
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whuber♦Jun 24 '13 at 17:14

@whuber On several occasions I've proposed solutions involving F#. The GIS people shunned it, suggesting that F# is for academics. That may be more of a reflection on the sometimes parochial (spatial-is-special) nature of the GIS community than of the actual technology. It reminded me a lot of the criticism I heard when someone proposed an AI approach to a GIS problem in the early 90's, using Cyc to illustrate that AI is ready for prime time.
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Kirk KuykendallJun 24 '13 at 17:59